Autoencoder Reconstruction of Cosmological Microlensing Magnification Maps by Somayeh Khakpash, Federica B. Bianco, Georgios Vernardos, Gregory Dobler, Charles Keeton

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A Deep Learning-Based Time-Frequency Scheme for Ship Detection Using HFSWR by Da Huang, Hao Zhou, Yingwei Tian, Zhiqing Yang, Weimin Huang

“…Compact High frequency surface wave radar (HFSWR) has been widely used in remote sensing of oceanic dynamics and ship targets due to its convenient deployment and low cost. However, when using a constant false alarm rate (CFAR) detector, these systems experience performance degradation primarily because of echo nonstationarity. …”
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Artificial Intelligence based Multi-sensor COVID-19 Screening Framework by Rakesh Chandra-Joshi, Malay Kishore-Dutta, Carlos M. Travieso

“… Many countries are struggling for COVID-19 screening resources which arises the need for automatic and low-cost diagnosis systems which can help to diagnose and a large number of tests can be conducted rapidly. …”
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A Hybrid Deep Learning Framework for Deepfake Detection Using Temporal and Spatial Features by Fazeel Zafar, Talha Ahmed Khan, Salas Akbar, Muhammad Talha Ubaid, Sameena Javaid, Kushsairy Abdul Kadir

“…Furthermore, the model achieves an impressive balance between accuracy and computational efficiency, attaining 92.45% testing accuracy with a lightweight computational cost of 0.45 GFLOPs, making it a highly practical choice for real-world deployment.…”
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Improving vertical detail in simulated temperature and humidity data using machine learning by Joana D. da Silva Rodrigues, Cyril J. Morcrette

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Compressed CNN Plant Leaf Ｒecognition Model Fused with Bayesian by YAN Ming, ZHU Liang-kuan, JING Wei-peng

“…Aiming at the problem that there are many parameters in the process of plant leaf recognition and it is easy to produce over-fitting，in order to reduce the cost of storage and calculation，this paper proposes a plant leaf recognition convolutional neural network model based on Bayesian fusion. …”
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An automated platform to detect, assess, and quantify deterioration in concrete structures by Ibrahim Odeh, Behrouz Shafei

“…To move toward reducing inspection time, cost, and human error, the current study developed a deep convolutional neural network model tailored for detecting and quantifying deterioration in concrete structures. …”
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HALF: Histogram of Angles in Linked Features for 3D Point Cloud Data Segmentation of Plants for Robust Sensing by Hidenori Takauji, Naofumi Wada, Shun’ichi Kaneko, Takanari Tanabata

“…To enhance robustness and interpretability, we extend HALF to a convolution-based mathematical framework and introduce the Sequential Competitive Segmentation Algorithm (SCSA) for phytomer-level classification. …”
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Colorectal Cancer Detection Tool Developed with Neural Networks by Alex Ede Danku, Eva Henrietta Dulf, Alexandru George Berciu, Noemi Lorenzovici, Teodora Mocan

“…The objective of this study is to develop a practical, low-cost, AI-based decision-support tool that integrates clinical test data (blood/stool) and, if needed, colonoscopy images to help reduce misdiagnosis and improve early detection of colorectal cancer for clinicians. …”
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Assessment of Scientific Creative-Potential by Near-Infrared Spectroscopy Using Brain-Network-Based Deep-Fuzzy Classifier by Sayantani Ghosh, Amit Konar, Atulya K. Nagar

“…The novelty of the classifier lies in: i) design of an enhanced graph convolution operation that encapsulates local and global structural information from the input graph, ii) use of the Smish activation function to improve performance, iii) inclusion of a one-dimensional spatial convolution layer for preserving relevant information within convolved embeddings, iv) design of a novel mapping function to mitigate uncertainty among the spatial convolved vectors in the type-2 fuzzy layer, and v) application of Takagi-Sugeno-Kang (TSK)-based fuzzy reasoning to reduce computational cost. …”
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Real-Time Human Action Recognition With Dynamical Frame Processing via Modified ConvLSTM and BERT by Raden Hadapiningsyah Kusumoseniarto, Zhi-Yuan Lin, Shun-Feng Su, Pei-Jun Lee

“…A novel architecture with a modified convolutional long short-term memory (ModConvLSTM) with pose heatmaps as input features is proposed to achieve human action recognition without a fixed frame number. …”
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Improving Medical Image Quality Using a Super-Resolution Technique with Attention Mechanism by Dong Yun Lee, Jang Yeop Kim, Soo Young Cho

“…Sharp and detailed images are essential for accurate diagnoses, but acquiring high-resolution medical images often demands sophisticated and costly equipment. To address this challenge, this study proposes a convolutional neural network (CNN)-based super-resolution architecture, utilizing a melanoma dataset to enhance image resolution through deep learning techniques. …”
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Recognition of Strawberry Powdery Mildew in Complex Backgrounds: A Comparative Study of Deep Learning Models by Jingzhi Wang, Jiayuan Li, Fanjia Meng

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Flat U-Net: An Efficient Ultralightweight Model for Solar Filament Segmentation in Full-disk Hα Images by GaoFei Zhu, GangHua Lin, Xiao Yang, Cheng Zeng

“…Existing models of filament identification are characterized by large parameter sizes and high computational costs, which limit their future applications in highly integrated and intelligent ground-based and space-borne observation devices. …”
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Prediction of microbe-drug associations using a CNN-Bernoulli random forest model by Zihao Song, Qingnuo Li, Jincheng Zhao, Qinggang Bu, Zekang Bian, Jia Qu

“…Since traditional wet-lab experiments are time-consuming and costly, computational models offer an efficient alternative for discovering potential applications of existing drugs against previously untested microbes. …”
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Recent technological developments allow for passive acoustic monitoring of Orthoptera (grasshoppers and crickets) in research and conservation across a broad range of temporal and... by David Bennett, Henning Nissen, Marc Andre Maschke, Heinrich Reck, Tim Diekötter

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Single Infrared Super-Resolution via a Shifted Full-Scale Non-Local Network by Honghong Lu, Zhenhua Li

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A Deep Learning Approach to Evaluating SISO-OFDM Channel Equalization by Saja S Hanoon, Hasan F Khazal, Thamer M Jamel

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A Surrogate Model for the Rapid Prediction of Factor of Safety in Slopes with Spatial Variability by Xitailang Cao, Shan Lin, Miao Dong, Quanke Hu, Hong Zheng

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Patient-Specific Detection of Atrial Fibrillation in Segments of ECG Signals using Deep Neural Networks by Jeyson A. Castillo, Yenny C. Granados, Carlos Augusto Fajardo Ariza

“…In Colombia, it is difficult to have access to an early diagnosis of AF because of the associated costs to the detection and the geographical distribution of cardiologists. …”
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